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  # Model description
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- This is a multivector retrieval model that is built upon the efficient [XTR](https://proceedings.neurips.cc/paper_files/paper/2023/hash/31d997278ee9069d6721bc194174bb4c-Abstract-Conference.html) architecture. The model utilizes [t5-base](https://huggingface.co/t5-base) encoder, and is finetuned on [MSMarco](https://huggingface.co/datasets/BeIR/msmarco) dataset for mutlivector retrieval using XTR objetive.
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  # Overview
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  *Data*: MSMarco
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  # Intented use
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- This model can be utilized for text retrieval (IR). You can find detailed instructions and examples on how to use this model for text retrieval in the [documentation](https://github.com/primeqa/primeqa/blob/xtr/notebooks/ir/dense/xtr_retrieval.ipynb) provided.
 
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  # Model description
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+ This is a multivector retrieval model that is built upon the efficient [XTR](https://proceedings.neurips.cc/paper_files/paper/2023/hash/31d997278ee9069d6721bc194174bb4c-Abstract-Conference.html) architecture. The model utilizes [t5-base](https://huggingface.co/t5-base) encoder, and is finetuned on [MSMarco](https://huggingface.co/datasets/BeIR/msmarco) dataset with XTR objective.
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  # Overview
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  *Data*: MSMarco
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  # Intented use
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+ This model can be utilized for text retrieval (IR). You can find detailed instructions and examples on how to use this model for text retrieval in the documentation [here](https://github.com/primeqa/primeqa/blob/xtr/notebooks/ir/dense/xtr_retrieval.ipynb).